Mustafa Güneş

Fuzzy Multi-criteria Decision Making Method for Machine Selection

The selection of appropriate machines is one of the most crucial decisions for a manufacturing company to develop an efficient production environment. The aim of this study is to propose a fuzzy approach for selecting the best machine. This paper is based on a fuzzy extension of the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. In this method, the ratings of various alternatives versus various subjective criteria and the weights of all criteria are assessed in linguistic variables represented by fuzzy numbers. Fuzzy numbers try to resolve the ambiguity of concepts that are associated with human being’s judgments. To determine the order of the alternatives, closeness coefficient is defined by calculating the distances to the fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS). By using fuzzy TOPSIS, uncertainty and vagueness from subjective perception and the experiences of decision maker can be effectively represented and reached to a more effective decision.

Fuzzy Goal Programming and an Application of Production Process

Nowadays, information and advanced technology are commonly used. It is certain that the societies which benefit from information and technology will be more successful in this world where global competition is intensive. So managers must decide fast and right in the global competition. The way to decide fast and right is to benefit from the scientific methods that increase options and reduce uncertainty. Recently it has seen that decisions are mostly being made, in one sense in fuzzy. So the importance of fuzzy goal programming, one of operation research models including fuzzy, has been increasing day by day. The aim of this article is to examine fuzzy goal programming model which is one of the models providing the best decision-making under fuzzy. The article, in the direction of this aim, consists of five parts. In the first part, there is a general introduction about the subject. In the second part, it’s mentioned about the fuzzy sets and the basic concepts of the membership function. In the third part fuzzy goal programming that has common usage area is explained. In the fourth part, fuzzy goal programming has applied to a firm with profit and sale goals. In the last part, conclusions and findings have been interpreted.

The Usage of Fuzzy Quality Control Charts to Evaluate Product Quality and an Application

The quality improvement is of the great importance to strength a competitive position in our markets today. Though improving the quality, shrinkages and so production costs decrease and the customers obtain the appropriate products and services to use. Models are needed for transferring information from one place to another quickly, decreasing and even for eliminating it in the complex subjects. These vagueness is explained by the fuzzy set concept which is useful for making optimal decision under uncertainty and which is accepted as inference based on a specific logic. Control charts have an efficient usage field to keep the process under control. Control charts are accepted as graphical analysis method which determines the products whether to remain in the acceptable limits or not and as a graphical analysis method which gives a signal in the case of product to be out of these limits. In this study by revealing basic idea and principles behind the control charts usage and the improvement; they are combined with fuzzy quality control charts and an application about their usage is mentioned. As a result of the application, it’s possible to say that building fuzzy control charts have a more flexible and a more appropriate mathematical description concept and have more reasonable results than the traditional quality chart techniques.